Is it possible to derive meaning from text by providing multiple ways of saying the same thing to a neural network?
No, it will not derive patterns of meaning, as the network has no understanding of language. What will happen, is that it picks up surface features (usually letter sequences) which are common between sentences with the same (or a similar) meaning.

This approach is often used in chatbots for intent recognition. Sometimes it picks up subtle patterns that humans would not notice, but they are also often not reliable: you get wrong classifications without knowing why.

Having said that, it works fine if you want to distinguish between a limited number of different intents (you don't even need a lot of training examples &mdash; 4 to 5 examples are often sufficient if they are well-selected). In this fairly limited scenario yes, otherwise no.